Randomization inference in shift share designs with an application in banking

Detalhes bibliográficos
Autor(a) principal: Oliveira, Raoni Ribeiro Aredes de
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
Texto Completo: https://hdl.handle.net/10438/33329
Resumo: This Master Thesis is comprised of two parts. The first one, presented in Chapter 1, is a theoretical advance in econometrics for Shift-share Designs, based on joint work with Luis Alvarez and Bruno Ferman, "Randomization Inference Tests for Shift-Share Designs" (see the reference Alvarez et al., 2022). It shows that, by choosing a properly studentized statistic for performing Randomization Inference, we are able to (i) control size in finite samples under relatively strong hypotheses, such as homogeneous treatment effects and known assignment process, and (ii) control size asymptotically under milder hypotheses, such as a "well-behaved" treatment heterogeneity and randomization distribution, even if it is different from the original assignment process. The second part, in Chapter 2, is an empirical application of this technique to the expansion of the physical bank network in Brazil during the commodity boom of the 2000's and 2010's. It seeks to measure to what extent the increase in the number of branches in the period was a response to greater economic activity. This is of interest because, at the time, the physical network was a vector of financial inclusion. Understanding the extent to which this was spurred by exogenous demand shocks may be informative for future policy.
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spelling Oliveira, Raoni Ribeiro Aredes deEscolas::EESPPossebom, Vitor AugustoSant'Anna, Pedro H. C. G.Ferman, BrunoMata, Daniel da2023-03-14T15:20:17Z2023-03-14T15:20:17Z2023-03-06https://hdl.handle.net/10438/33329This Master Thesis is comprised of two parts. The first one, presented in Chapter 1, is a theoretical advance in econometrics for Shift-share Designs, based on joint work with Luis Alvarez and Bruno Ferman, "Randomization Inference Tests for Shift-Share Designs" (see the reference Alvarez et al., 2022). It shows that, by choosing a properly studentized statistic for performing Randomization Inference, we are able to (i) control size in finite samples under relatively strong hypotheses, such as homogeneous treatment effects and known assignment process, and (ii) control size asymptotically under milder hypotheses, such as a "well-behaved" treatment heterogeneity and randomization distribution, even if it is different from the original assignment process. The second part, in Chapter 2, is an empirical application of this technique to the expansion of the physical bank network in Brazil during the commodity boom of the 2000's and 2010's. It seeks to measure to what extent the increase in the number of branches in the period was a response to greater economic activity. This is of interest because, at the time, the physical network was a vector of financial inclusion. Understanding the extent to which this was spurred by exogenous demand shocks may be informative for future policy.Esta Dissertação de Mestrado é composta de duas partes. A primeira, apresentada no Capítulo 1, é uma contribuição teórica em econometria para Shift-Share Designs, baseada no trabalho feito em conjunto com Luis Alvarez and Bruno Ferman, "Randomization Inference Tests for Shift-Share Designs" (veja a referência Alvarez et al., 2022). Ela mostra que, escolhendo uma estatística adequadamente estudentizada para realizar Inferência por Randomização, nós somos capazes de (i) controlar o tamanho do teste em amostras finitas sob condições relativamente fortes, como efeitos homogêneos de tratamento e distribuição conhecida dos choques, e (ii) controlar o tamanho do teste assintoticamente sob condiçõesmenos exigentes, como heterogeneidade dos efeitos de tratamento e distribuição dos choques usada nas simulações (randomização) "bem comportados", ainda que essa última seja diferente da distribuição verdadeira do processo gerador de dados. A segunda parte, no Capítulo 2, é uma aplicação empírica dessa técnica à expansão da rede física de agências bancárias no Brasil durante o boom de commodities dos anos 2000 e 2010. Tenta-se medir até que ponto o aumento do número de agências foi uma resposta à maior atividade econômica. Trata-se uma pergunta interessante pois, à época, essa rede física foi um vetor de inclusão financeira. Entender até que ponto isso foi estimulado por um choque exógeno de demanda pode ser informativo para políticas públicas futuras.engShift-share designsRandomization inferenceBrazilBank branch networkInferênciaRede bancáriaAgênciasEconomiaEconometriaEstatística matemáticaBancos - BrasilDesenvolvimento econômicoRandomization inference in shift share designs with an application in bankinginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVORIGINALssri_raoni_2023_ABNT_v4.pdfssri_raoni_2023_ABNT_v4.pdfPDFapplication/pdf879881https://repositorio.fgv.br/bitstreams/e9c42aa7-ce00-4065-8156-80b3092366d2/downloadd74449210f9ee604dfbd67976d02be8cMD51LICENSElicense.txtlicense.txttext/plain; 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dc.title.eng.fl_str_mv Randomization inference in shift share designs with an application in banking
title Randomization inference in shift share designs with an application in banking
spellingShingle Randomization inference in shift share designs with an application in banking
Oliveira, Raoni Ribeiro Aredes de
Shift-share designs
Randomization inference
Brazil
Bank branch network
Inferência
Rede bancária
Agências
Economia
Econometria
Estatística matemática
Bancos - Brasil
Desenvolvimento econômico
title_short Randomization inference in shift share designs with an application in banking
title_full Randomization inference in shift share designs with an application in banking
title_fullStr Randomization inference in shift share designs with an application in banking
title_full_unstemmed Randomization inference in shift share designs with an application in banking
title_sort Randomization inference in shift share designs with an application in banking
author Oliveira, Raoni Ribeiro Aredes de
author_facet Oliveira, Raoni Ribeiro Aredes de
author_role author
dc.contributor.unidadefgv.por.fl_str_mv Escolas::EESP
dc.contributor.member.none.fl_str_mv Possebom, Vitor Augusto
Sant'Anna, Pedro H. C. G.
dc.contributor.author.fl_str_mv Oliveira, Raoni Ribeiro Aredes de
dc.contributor.advisor1.fl_str_mv Ferman, Bruno
Mata, Daniel da
contributor_str_mv Ferman, Bruno
Mata, Daniel da
dc.subject.eng.fl_str_mv Shift-share designs
Randomization inference
Brazil
Bank branch network
topic Shift-share designs
Randomization inference
Brazil
Bank branch network
Inferência
Rede bancária
Agências
Economia
Econometria
Estatística matemática
Bancos - Brasil
Desenvolvimento econômico
dc.subject.por.fl_str_mv Inferência
Rede bancária
Agências
dc.subject.area.por.fl_str_mv Economia
dc.subject.bibliodata.por.fl_str_mv Econometria
Estatística matemática
Bancos - Brasil
Desenvolvimento econômico
description This Master Thesis is comprised of two parts. The first one, presented in Chapter 1, is a theoretical advance in econometrics for Shift-share Designs, based on joint work with Luis Alvarez and Bruno Ferman, "Randomization Inference Tests for Shift-Share Designs" (see the reference Alvarez et al., 2022). It shows that, by choosing a properly studentized statistic for performing Randomization Inference, we are able to (i) control size in finite samples under relatively strong hypotheses, such as homogeneous treatment effects and known assignment process, and (ii) control size asymptotically under milder hypotheses, such as a "well-behaved" treatment heterogeneity and randomization distribution, even if it is different from the original assignment process. The second part, in Chapter 2, is an empirical application of this technique to the expansion of the physical bank network in Brazil during the commodity boom of the 2000's and 2010's. It seeks to measure to what extent the increase in the number of branches in the period was a response to greater economic activity. This is of interest because, at the time, the physical network was a vector of financial inclusion. Understanding the extent to which this was spurred by exogenous demand shocks may be informative for future policy.
publishDate 2023
dc.date.accessioned.fl_str_mv 2023-03-14T15:20:17Z
dc.date.available.fl_str_mv 2023-03-14T15:20:17Z
dc.date.issued.fl_str_mv 2023-03-06
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